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Clearing the Confusion: AI vs Machine Learning vs Deep Learning Differences
Raise your hand if you’ve been caught in the confusion of differentiating artificial intelligence (AI) vs machine learning (ML) vs deep learning (DL)… Bring down your hand, buddy, we can’t see it!
Andrey Bulezyuk, who is a German-based computer expert and has more than five years of experience in teaching people how artificial intelligence systems work, says that “practitioners in this field can clearly articulate the differences between the three closely-related terms.” Therefore, is there a difference between artificial intelligence, machine learning, and deep learning?
So, AI is the all-encompassing concept that initially erupted, then followed by ML that thrived later, and lastly DL that is promising to escalate the advances of AI to another level.
Let’s dig deeper so that you can understand which is better for your specific use case: artificial intelligence, machine learning, or deep learning.
Whenever a machine completes tasks based on a set of stipulated rules that solve problems (algorithms), such an “intelligent” behavior is what is called artificial intelligence.
For example, here is a table that identifies the type of fruit based on its characteristics: As you can see on the table above, the fruits are differentiated based on their weight and texture.
Just like we use our brains to identify patterns and classify various types of information, deep learning algorithms can be taught to accomplish the same tasks for machines.
Whenever we receive a new information, the brain tries to compare it to a known item before making sense of it — which is the same concept deep learning algorithms employ.
Data Science, Machine Learning and Artificial Intelligence for Art
Data Science, Machine Learning and Artificial Intelligence are fields from computer science that have already penetrated many industries and companies around the world.
This blog post will explain how state-of-the-art data science, machine learning (ML) and artificial intelligence (AI) methods are being used in the art market by Thread Genius, a firm acquired by Sotheby’s, the oldest international auction house in the world (Est.
Artificial Intelligence is when computational tools start to possess cognitive abilities — for the purposes of this post, AI will refer to “deep learning” techniques that use artificial neural networks.
Our initial efforts involve software development of large scale data pipelines for cleaning and standardizing the troves of historical Sotheby’s data so that we can undertake data analysis and apply ML and AI at scale.
Sotheby’s has some of the best data in the art market related to historical transactions, individual’s preferences for art at every price point, images, object and artwork information, and much more.
The dataset uses the purchase prices of the same painting at two distinct moments in time (i.e., repeat-sales) to measure the change in the value of unique works of art.
By bringing all three of these missions together, our aim is to improve operational efficiency and build the best data products in the art market so that our clients can get the best experience and transparent information when engaging with art at Sotheby’s.
We primarily use Google Cloud Platform for all of our work — everything from data cleaning in Dataprep, from data processing and standardization in Dataflow, to data storage in Big Query, data analysis in Datalab, and finally, ML and AI using GCP’s whole suit of machine learning capabilities.
We are excited to be applying advanced machine learning and artificial intelligence in the art market and working directly with our Specialists at Sotheby’s so that we can create the best data products in the industry.
If you have a background in data science, machine learning, NLP and/or AI and are interested in changing the world, feel free to reach out to us for a chat, we’re always interested in speaking with you, our audience.
- On Tuesday, December 10, 2019
Artificial Intelligence Vs Machine Learning Vs Data science Vs Deep learning
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